The Growth and Decay of Intense GNSS Amplitude and Phase Scintillation During Non‐Storm Conditions
Bibliographic record
Abstract
Abstract A multi‐instrument study is conducted at the dayside polar ionosphere to investigate the spatio‐temporal evolution of scintillation in Global Navigation Satellite System (GNSS) signals during non‐storm conditions. Bursts of intense amplitude and phase scintillation started to occur at 9 MLT and persisted for more than 1 hour implying the simultaneous existence of Fresnel and large‐scale sized irregularities of significant strength in the pre‐noon sector. Measurements from the EISCAT radar in Svalbard (ESR) revealed the presence of dense plasma structures with significant gradients in regions of strong Joule heating/fast flows and soft precipitation when scintillation was enhanced. Plasma structuring down to Fresnel scales were observed both in the auroral oval as well as inside the polar cap with the associated amplitude scintillation exhibiting similar strengths regardless of whether the density structures were in regions of active auroral dynamics or not. The observations are placed within the context of different sources of free energy, providing insights into the important mechanisms that generate irregularities capable of perturbing GNSS signal properties in the dayside ionosphere. Furthermore, a strong negative excursion in the interplanetary magnetic field (IMF) component during the northward turning of led to the transport of a depleted region of plasma density into the post‐noon sector that significantly weakened both amplitude and phase scintillation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".